Let us go back where we stopped developing our mapping techniques yesterday: Our Corona Map. This is just a super short repetition of what was just presented. No worries, we’re going to have some time to improve your maps.

1

Recreate a simple Covid-19 map as already created yesterday but use ggplot2 this time.

They don’t have to perfectly match but:

  • Use either the cases per 100.000 inhabitants or cases per 100.000 inhabitants in the last 7 days.
  • Choose a color palette.
  • Name your legend and change its position.
  • Your map should have a title. 
# For importing the data, you can ue this code:
library(dplyr)
library(sf)

attributes_districts <-  read.csv("./data/attributes_districts.csv", 
                                  header = T, fill = T, sep = ",") 
german_districts_enhanced <- st_read(dsn = "./data",
                           layer = "GER_DISTRICTS") %>% 
                           rename(., district_id = id) %>% 
                          st_transform(., crs = 3035) %>% 
                          left_join(., attributes_districts, by = "district_id")

solution 

# load libraries
library(ggplot2)


# build map
covid_map <-
ggplot() +
  geom_sf(data = german_districts_enhanced, 
          aes(fill = cases_per_100k), 
          color = NA) + 
  scale_fill_viridis_c(option = "plasma",
                       direction = -1,
                       name = "Covid-19 Cases per 100k") + 
  theme(legend.position = "left") +
  labs(title="Covid-19 Map",   
       subtitle= "German Federal Elections 2017")

2

Now we want to add another layer to see if enough hospitals are located in the Covid-19 high risk zones of Germany.

  • Add the the hospital layer to the map
  • Change the color of the points
  • Save the plot including hospitals as pdf

For an extra challenge: The hospital shapefile contains information on the number of beds in each hospital. Can you change the size of hospital dots according to the number of beds?

Make sure that the CRS of your hospital layer is defined correctly!

You need to define size = beds as aethetics of the new layer.

The variable beds is a character but needs to be numeric.

solution 

# import point layer hospital sf
hospitals_sf <- read.csv("./data/hospital_points.csv", header = T, fill = T, sep = ",") %>%
                st_as_sf(., coords = c("X", "Y"),
                  crs = 3035)
                
# add layer to map
covid_map <-
  ggplot() +
   geom_sf(data = german_districts_enhanced, 
          aes(fill = cases_per_100k), 
          color = NA) + 
   scale_fill_viridis_c(option = "plasma",
                       direction = -1,
                       name = "Covid-19 Cases per 100k") + 
    theme(legend.position = "left") +
    labs(title="Covid-19 Map") +
    geom_sf(data = hospitals_sf,
         aes(size = as.numeric(beds)))

# save map
ggsave("./data/own_material/covid_map.pdf", covid_map, dpi = 300)